IPHARMA Clinical Trials Russia Forum

1. EFFECTIVE CLINICAL
TRIAL DESIGN
Natalia Vostokova
Chief Operating Officer
IPHARMA LLC
November 24, 2015

2. 2
WORKSHOP SUBJECT
• Effective phase 2 and 3 clinical study design
• Adaptive design implementation in local
clinical studies

3. 3
WORKSHOP AGENDA
• Phase 2 and 3 study concepts
• What is adaptive design?
• Adaptive design advantages and risks
• Next-in-class drugs
• Examples of successful adaptive design
implementation

4. 4
SCIENTIFIC EXPERIMENT
Objective
ResultDesign

5. 5
PHASE 2
= pilot trial
• Objectives  Results
• works or doesn’t work
• optimum dosing schedule
• preliminary efficacy data for planning phase 3
• Design – fast and demonstrative

6. 6
PHASE 2
Randomization
Dose 1
Dose 2
Dose 3
Placebo Response

7. 7
PHASE 3
= pivotal trial
• Objectives  Results
• Hypothesis testing with pre-defined predictable
result
• Design – with minimal risk

8. 8
PHASE 3
Randomization
Investigational
product
«Gold standard»
Response

9. 9
STUDY DESIGN DEVELOPMENT
PRINCIPLES
• Primary endpoint
• Binary (response rate)
• Continues (change of parameter)
• Hypothesis
• Non-inferiority
• Equivalence
• Superiority
Study objective
Drug mode of
action
Primary endpoint
Hypothesis
H0 ↔ Hа
Sample sizing
calculation
Treatment length
and procedures
Data collection
Decision-making
algorithm
Control group
expected value

10. 10
CLINICAL STUDY DESIGN
Adaptive design
Classic design«Prehistoric design»

11. 11
ADAPTIVE DESIGN
• Study that allows modifying any design or
hypothesis aspect based on the interim data
analysis
• in accordance with a pre-defined plan
• in preselected timepoints
• blinded or unblinded
• with or without a hypothesis testing

12. 12
WELL-UNDERSTOOD ADAPTIVE
DESIGNS
• Adaptation of study eligibility criteria based on analyses of
pretreatment (baseline) data
• Adaptations to maintain study power based on blinded
interim analyses of aggregate data
• Adaptations based on interim results of an outcome unrelated
to efficacy
• Adaptations using group sequential methods and unblinded
analyses for early study termination because of either lack of
benefit or demonstrated efficacy
• Adaptations in the data analysis plan not dependent on within
study, between-group outcome differences

13. 13
LESS-UNDERSTOOD ADAPTIVE
DESIGNS
• Adaptations for dose selection studies*
• Adaptive randomization based on relative treatment group
responses
• Adaptation of sample size based on interim-effect size
estimates
• Adaptation of patient population based on treatment-effect
estimates
• Adaptation for endpoint selection based on interim estimate
of treatment effect
• Adaptation of multiple-study design features in a single
study*
• Adaptations in non-inferiority studies

14. 14
ADAPTIVE DESIGN ADVANTAGES
• More efficient data collection
• Shorter study duration
• Less number of patients
• Increasing a probability of success in achieving
the study objectives
• Improved understanding of the investigational
product’s effects
Optimization of drug development compared to
the classic non-adaptive methodology

15. 15
ADAPTIVE DESIGN RISKS
• Risks of bias
• Misinterpretation of the interim analysis
• Non-achievement of the study objectives

16. 16
ADAPTIVE DESIGN RISKS
MITIGATION
• Well-planned study
• Well-considered statistical validity
• α-adjustment for a multiplicity
• Minimal clearly planned adaptation
• Pre-scheduled modification of the study parameters
• Without correction of the statistical methods
• Appropriate use
• Data Monitoring Committee (DMC)

17. 17
NEXT-IN-CLASS DRUGS
• Original patented drugs
• Affects the well-known biotargets
• Similar to the existing drugs in structure and mode of
action
• High predictability of effects in humans
• Possible achievement of better results owing to
«improvement» of the original molecule
• Less expensive and shorter timelines for development
 Low-risk R&D strategy

18. 18
MINISTRY OF INDUSTRY AND
TRADE PROGRAM
DRAFT
Government of the Russian Federation
Regulation
as of _______ 2015 № _______
Concerning approval of the rules of granting subsidies from the federal
budget to Russian organizations on partial reimbursement for
implementation of the projects in development of innovative analogues of
pharmaceuticals similar in pharmacotherapeutic action
= separate block of the MIT projects oriented on the next-in-class
drugs development

19. 19
STUDY PLANNING FOR
NEXT-IN-CLASS DRUGS
• Possible use of data of other drugs of the same
pharmacological class for planning the study
(hypothesis, sample calculation, endpoints)
• Comparison with the best-in-class drug
• Non-inferiority study
• Possible adaptive design

20. 20

21. EFFICACY ASSESSMENT OF
DIFFERENT DRUG DOSING
REGIMENS
Mono- and combination therapy

22. 22
TYPE 2 DIABETES MELLITUS
DPP-4 INHIBITOR
Screening Monotherapy
12 weeks
Combination therapy
24 weeks
Follow-up
Gosogliptin  Gosogliptin+Metformin
Vildagliptin  Vildagliptin+Metformin
STAGE 1 STAGE 2
Interim analysis
Final analysis

23. 23
PATIENTS ALLOCATION
Stage 2
Combination
therapy
Stage 1
Monotherapy
Randomization
299 treatment naïve
patients with T2DM
Gosogliptin
N=149
Gosogliptin +
Metformin
N=122
Vildagliptin
N=150
Vildagliptin +
Metformin
N=114
~ 20% didn't roll-over to Stage 2

24. 24
INTERIM AND FINAL ANALYSIS
∆HbA1c, % Gosogliptin Vildagliptin
Monotherapy (W12-W0) -0.93% -1.03%
∆
[97.5% CI]
0,104%
[-0,133 to 0,342]
upper bound of
97.5% CI < 0.4
Combination (W36-W0) -1.29% -1.35%
∆
[97.5% CI]
0,057%
[-0,187 to 0,300]
upper bound of
97.5% CI < 0.4

25. DOSE FINDING AND EFFICACY
ASSESSMENT
Interim analysis using statistics for
small sample size

26. 26
PREVENTION OF TROMBOSIS
DIRECT FACTOR Xa INHIBITOR
Screening
Randomization
Kneereplacement
Hospital treatment
Endoftreatment
Follow-up
Day D-14…-1 D0 D1 D4 D7 D12±2 D21 D42
1) Tearxaban twice a day (morning and evening)
(first dose in the evening > 10 hours after surgery)
- 50 mg
- 100 mg optimal daily dose selection at Stage 1
- 150 mg
2) Enoxaparin 40 mg s/c
(1st dose in the evening before the surgery)

27. 27
PATIENT ALLOCATION
Stage 2
Efficacy
assessment
Stage 1
Dose-finding
Randomization
190 patients with
knee replacement
(prevention of VTE)
Tearxaban 50 mg
N=21
Tearxaban 100 mg
N=21
Tearxaban 100 mg
N=21+52=73
Tearxaban 150 mg
N=20
Enoxaparin 40 mg
N=22
Enoxaparin 40 mg
N=22+54=76
Interim analysis Final analysis

28. 28
INTERIM ANALYSIS
(80 PATIENTS, VTE, SIMON'S MINIMAX)
Tearxaban
Enoxaparin
N = 2250 mg
N = 21
100 mg
N = 21
150 mg
N = 20
Cumulative VTE 5 (23.8%) 3 (14.3%) 1 (5.0%) 5 (22.7%)
DVT frequency 5 (23.8%) 3 (14.3%) 1 (5.0%) 4 ( 18.2%)
Symptomatic VTE frequency (DVT, PE) 0 (0.0%) 0 (0.0%) 0 (0.0%) 2 (9.1%)
Non-fatal PE frequency 0 (0.0%) 0 (0.0%) 0 (0.0%) 1 (4.5%)
Cumulative hemorrhagic complications
frequency
3 (14.3%) 1 (4.8%) 4 (19.0%) 1 (4.5%)
Major and clinical significant non-major
bleeding frequency
2 (9.5%) 0 (0.0%) 1 (4.8%) 1 (4.5%)

29. 29
FINAL ANALYSIS
(150 PATIENTS, VTE, NON-INFERIORITY)
TeaRX 100 mg
N = 73
Enoxaparin
N = 76
Cumulative VTE 14 (19.2%) 21 (27.6%)
∆
[97.5% CI]
8.45%
[-3.01%; 19.59%]
Lower bound of
97.5% CI > -5.00%
DVT frequency 14 (19.2%) 20 (26.3%)
Symptomatic VTE frequency (DVT, PE) 0 (0.0%) 2 (2.6%)
Non-fatal PE frequency 0 (0.0%) 1 (1.3%)
Cumulative hemorrhagic complications frequency 1 (1.4%) 2 (2.6%)
Major and clinical significant non-major
bleeding frequency
0 (0.0%) 2 (2.6%)

30. DOSE FINDING AND EFFICACY
ASSESSMENT
Interim analysis with a surrogate
endpoint

31. 31
HIV, NNRTI
SCREENING
Investigational therapy administration
Follow-up
VM-1500 20 mg + ART
VM-1500 40 mg + ART
Efavirenz 600 mg + ART
V1 B2 V6 V8 V10 B11
W-2 W0 W12 W24 W48 W52
↑ ↑ ↑ ↑
Randomization Surrogate endpoint
(interim analysis)
Primary endpoint
(final analysis)
End of
treatment

32. 32
PATIENTS ALLOCATION
Stage 2
Efficacy assessment
Stage 1
Dose-finding
Randomization
150 treatment
naïve patients
with HIV
VM-1500 20 mg
N=30
VM-1500 40 mg
N=30
VM-1500 40 mg
N=30+30=60
Efavirenz 600 mg
N=30
Efavirenz 600 мг
N=30+30=60
Interim analysis Final analysis

33. 33
INTERIM ANALYSIS
(90 PATIENTS, HIV RNA< 400 COPIES/ML ON WEEK 12,
NON-INFERIORITY)
Patients with HIV RNA < 400 copies/ml
Week
VM-1500 20 mg
N=30
VM-1500 40 mg
N=29
EFV 600 mg
N=27
W12 28 (93.3%) 25 (86.2%) 22 (81.5%)
∆
[97.5% CI]
11.85%
[-2.59%; 26.92%]
4.73%
[-11.50%; 20.83%]
Lower bound
97.5% CI > -15.00%
* Final analysis at Q1 2016

34. 34
CONCLUSION
• Implementation of adaptive design provides
an opportunity to improve timeline and
resources when developing next-in-class
innovative drugs

35. 35
THANK YOU FOR YOUR ATTENTION
Natalia Vostokova
Chief Operating Officer
7 Nobel street
«Skolkovo» Innovation Center
Moscow, 143026, Russia
Mobile: +7 (926) 098-3633
Phone: +7 (495) 276-1143
Fax: +7 (495) 276-1147
E-mail: nv@ipharma.ru
Web-site: www.ipharma.ru